Talend-Core-Developer Questions and Answers

Comprehensive and Detailed Explanation:

The defaultREST endpoint port for tRESTRequest in Talend Studio is 8090.

Port 8090 (Correct Answer - Option D):

When running a REST service insideTalend Studio, the default listening port is8090.

This can be changed in the component settings if required.

Other port options explained:

5040 & 5070: Not default ports used for Talend REST services.

8040: Used inTalend Runtime, not in Studio.

To reuse a job named testJob from a referenced project named project_ref in your main job, you need to navigate to @Referenced project, @project_ref, Job Designs, Standard, then select testJob. A referenced project is a project that can be accessed from another project in read-only mode. You can add a referenced project to your main project by using the Project Settings window in Talend Studio. You can then browse the items (such as jobs, metadata, routines, etc.) of the referenced project in the Repository tree view under the @Referenced project node. You can drag and drop any item from the referenced project to your main job design workspace.

You do not need to use import items, create standard job, or navigate to Metadata options. These options are not used to reuse jobs from referenced projects. The import items option is used to import items (such as jobs, metadata, routines, etc.) from an archive file that can be exported from another project or workspace. The create standard job option is used to create a new job with a name and a description. The Metadata node in the Repository tree view is used to store and manage metadata definitions for various data sources (such as databases, files, web services,etc.). References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Referenced projects - 7.3]

Comprehensive and Detailed Explanation:

In Talend Management Console (TMC), aplanis a sequence of tasks executed in a defined order. The types of tasks that can be added to a plan include:​

Jobs (Option D):Standard data integration tasks designed in Talend Studio.​

Big Data tasks (Option B):Tasks involving big data processing.​

Routes (Option C):Tasks related to messaging routes.​

However,Data services (Option A)refer to web services and are not typically added as tasks within a plan.​

Comprehensive and Detailed Explanation:

After publishing a Job from Talend Studio to Talend Cloud, you can execute it using the Talend Management Console (TMC) by following these steps:​

Add a task and then run the task (Option A):

In TMC, navigate to theManagementsection and selectTasks.​

Click onAdd Task, choose the published artifact (your Job), configure necessary parameters, and save the task.​

Once the task is created, you can run it manually or schedule it for execution.​

Select the artifact name, add and configure a task, then run the task (Option D):

In TMC, go to theArtifactssection to view your published Jobs.​

Select the desired artifact and click onAdd Task.​

Configure the task settings as needed and save it.​

After creating the task, you can execute it immediately or set up a schedule.​

Why not other options?

Option B:TMC does not support directly running a Job by clicking on the artifact name without first creating a task.​

Option C:While you can select and configure an existing task, the initial step requires creating the task associated with the artifact.​

Trace Debug and Java Debug are two modes that allow you to debug your jobs in Talend Studio. Trace Debug mode allows you to trace each row processed by your job components and see the values of each column in each row. Java Debug mode allows you to debug your job code in Java or Perl and see the values of each variable or expression in your code.

The characteristics that distinguish Trace Debug from Java Debug are:

Trace Debug mode allows row-by-row inspection of data flows, while Java Debug mode does not. Data flows are the links that show the data transfer between components in your job design workspace. In Trace Debug mode, you can see the data flow on each trace and inspect the values of each column for each row processed by your job. You can also use filters to display only the rows that match a condition or an expression. In Java Debug mode, you cannot see the data flow on each trace or inspect the values of each column for each row.

Trace Debug mode supports breakpoints based on input data condition, while Java Debug mode does not. Breakpoints are points where the execution of your job pauses and waits for your action. You can use breakpoints to inspect your data or debug your logic at specific points of your job execution. In Trace Debug mode, you can set breakpoints on traces based on a condition or an expression that involves input data columns. For example, you can set a breakpoint to pause your job when a customer name contains a certain string or when a product price exceeds a certain value. In Java Debug mode, you can only set breakpoints on lines of code based on a condition or an expression that involves variables or expressions.

The characteristics that do not distinguish Trace Debug from Java Debug are:

Both modes require a separate perspective. A perspective is a set of views and editors that are arranged in a specific way to support a specific task. In Talend Studio, you can switch between different perspectives, such as Integration, Debug, Profiling, etc. To use Trace Debug mode, you need to switch to the Debug perspective by clicking on the Open Perspective button and selecting Debug. To use Java Debug mode, you need to switch to the Java perspective by clicking on the Open Perspective button and selecting Java.

Neither mode requires Java development experience. Although Java Debug mode allows you to debug your job code in Java or Perl, you do not need to have Java development experience to use it. You can use the graphical interface of Talend Studio to design your job components and properties without writing any code. You can also use the Code view to see the generated code of your job in Java or Perl and modify it if needed. However, you do not need to write any code from scratch or understand all the details of the code to use Java Debug mode. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Trace Debug mode - 7.3], [Java Debug mode - 7.3]

Comprehensive and Detailed Explanation:

To manually pair a Remote Engine with Talend Cloud, you can set the pairing key using the following methods:​

In the Remote Engine web service page (Option B):

Access the Remote Engine's web interface, typically available at http://localhost:8043/configuration.​

Enter the pairing key obtained from the Talend Management Console.​

Click onPAIR REMOTE ENGINEto establish the connection.​

In the key configuration file of the engine (Option C):

Locate the preauthorized.key.cfg file in the Remote Engine's etc directory.​

Open the file and paste the pairing key into the remote.engine.pre.authorized.key parameter.​

Save the changes and restart the Remote Engine to apply the configuration.​

Why not other options?

Option A:Setting the pairing key in Talend Studio's preferences is not applicable for pairing a Remote Engine.​

Option D:While it's technically possible to pass the pairing key as a parameter in the engine's run script, it's not the standard or recommended method.​

To create an empty Joblet, you need to right-click on the Joblet Designs node in the Repository tree view and select Create Joblet option. This will open a dialog box where you can enter the name and description of your Joblet and select an icon for it. You can then design your Joblet by adding components and links to it in the Designer workspace.

You cannot create an empty Joblet by creating an empty job, then exporting it as a Joblet by right-clicking it in the Repository, creating an empty job and using the file menu to save it as Joblet, or right-clicking a space in the Designer and selecting refactor to Joblet. These methods are not available in Talend Studio and may cause errors or unexpected results. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Joblets - 7.3]

Tags are used to mark specific points in the development lifecycle of a project. This can be done for a variety of reasons, such as:

To mark the completion of a major feature or release

To mark the start of a new development phase (e.g., QA, production)

To mark a known good state of the codebase (e.g., before a risky change)

Tags can be used to create branches, which can then be used to develop and test new features or bug fixes. They can also be used to deploy the codebase to different environments (e.g., development, staging, production).

Examples of when to use a tag:

When you are ready to release a new version of your application to production.

When you have completed a major feature or milestone in the development of your application.

Before making a risky change to your codebase, such as a database migration or refactoring.

When you need to deploy your application to a different environment, such as staging or production.

Benefits of using tags:

Tags can help you to keep track of the different versions of your codebase.

Tags can help you to roll back to a previous version of your codebase if necessary.

Tags can help you to deploy your codebase to different environments.

Tags can help you to collaborate with other developers more effectively.

Comprehensive and Detailed Explanation:

In Talend Cloud Data Preparation, the platform is designed to handle large datasets efficiently by displaying a sample of the data to the user. By default, Talend Cloud Data Preparation can display up to 10,000 records from a dataset. This sampling approach ensures that users can interact with and analyze their data without performance issues that might arise from loading an entire large dataset into memory. Users have the option to view the first 10,000 records (Head sample) or 10,000 randomly selected records (Random sample) to get a representative understanding of the dataset's content. ​

Comprehensive and Detailed Explanation:

After enabling the Observability Metric Collector in Talend's configuration file (org.talend.ipaas.rt.observability.cfg), it's essential to set additional parameters to control the behavior of metric collection:​

Frequency (Option C):Determines how often metrics are collected. Setting this ensures that data is gathered at appropriate intervals for monitoring needs.​

Lifetime (Option D):Specifies how long the collected metrics are retained. This helps manage storage and ensures that outdated metrics are purged.​

Configuring these parameters ensures that the metric collection aligns with organizational requirements for monitoring and performance analysis.​

A Joblet is a reusable piece of a job that can be used in multiple jobs as a single component. A tRunJob component is a component that allows you to call another job as a subjob within a parent job. When comparing a Joblet to a tRunJob component, these statements are true:

A Joblet uses the same context variables of the job in which it is used, unlike a tRunJob component. A context variable is a variable that can store a value that can be changed at runtime or between different contexts. A Joblet inherits the context variables from the job that contains it and does not have its own context variables. A tRunJob component can pass context variables from the parent job to the child job, or use a specific context for the child job.

Building a Joblet typically requires the use of generic input and trigger components. A Joblet can have one or more input and output flows that connect it with other components in a job. To create these flows, you need to use generic input and trigger components, such as tJobletInput, tJobletOutput, tJobletTriggerInput, and tJobletTriggerOutput. These components allow you todefine schemas and triggers for your Joblet without depending on specific components.

The nested job called by a tRunJob component cannot use the same context variables of the job in which it is used. A nested job is a job that is called by another job using a tRunJob component. A nested job can have its own context variables or receive context variables from its parent job, but it cannot use the same context variables as its parent job. This means that if you have two context variables with the same name in both jobs, they will be treated as separate variables and will not share values.

These statements are false when comparing a Joblet to a tRunJob component:

The performance of tRunJob component is better than running an equivalent job using a Joblet. The performance of a Joblet is better than running an equivalent job using a tRunJob component. This is because a Joblet is integrated into the main code of the job and does not require launching another JVM process or loading another metadata object like a tRunJob component does. References: Talend Open Studio: Open-source ETL and Free Data Integration | Talend, [Joblets - 7.3], [tRunJob properties - 7.3], [Contexts - 7.3]